Finding de novo methylated DNA motifs.
Finding de novo methylated DNA motifs.
复制标题
寻找从头甲基化 DNA 基序。
DOI：
10.1093/bioinformatics/btz079
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发表时间：
2019
期刊：
影响因子：
--
通讯作者：
Wang,Wei
中科院分区：
文献类型：
--
作者：
Ngo,Vu;Wang,Mengchi;Wang,Wei
越来越多的证据表明，胞嘧啶上的甲基化和羟甲基化等核苷酸修饰会极大地影响转录因子（TF）的结合。然而，目前还缺乏一种具有搜索基序修饰的基序的功能的基序发现算法。在这项研究中，我们扩大了我们以前的基序发现管道Epigram提供systematicde novomotif发现和性能评估甲基化的DNA motifs.ResultsmEpigram优于MEME和DREME在模拟数据中，模仿各种基序富集的情况下发现修改的基序。此外，我们能够识别甲基化基序includingopsis DNA亲和纯化测序（DAP-seq）的数据，以前被证明含有这样的基序。当应用于H1和GM 12878中的TF ChIP-seq和DNA甲基化组数据时，我们的方法成功地鉴定了可以被TF或其辅因子识别的新型甲基化基序。我们还观察到TF的典型基序和新发现的甲基化基序之间的间距约束，这表明协同蛋白质对这些cis元件的操作识别。可用性和实施mEpigram程序可在http://wanglab.ucsd.edu/star/mEpigram.Supplementary信息补充数据可在Bioinformaticsonline。
MotivationIncreasing evidence has shown that nucleotide modifications such as methylation and hydroxymethylation on cytosine would greatly impact the binding of transcription factors (TFs). However, there is a lack of motif finding algorithms with the function to search for motifs with modified bases. In this study, we expand on our previous motif finding pipeline Epigram to provide systematicde novomotif discovery and performance evaluation on methylated DNA motifs.ResultsmEpigram outperforms both MEME and DREME on finding modified motifs in simulated data that mimics various motif enrichment scenarios. Furthermore we were able to identify methylated motifs inArabidopsisDNA affinity purification sequencing (DAP-seq) data that were previously demonstrated to contain such motifs. When applied to TF ChIP-seq and DNA methylome data in H1 and GM12878, our method successfully identified novel methylated motifs that can be recognized by the TFs or their co-factors. We also observed spacing constraint between the canonical motif of the TF and the newly discovered methylated motifs, which suggests operative recognition of thesecis-elements by collaborative proteins.Availability and implementationThe mEpigram program is available at http://wanglab.ucsd.edu/star/mEpigram.Supplementary informationSupplementary data are available atBioinformaticsonline.